Getting Connected to M-Health Technologies through a Meta-Analysis.

The demand for mobile e-health technologies (m-health) continues with constant growth, stimulating the technological advancement of such devices. However, the customer needs to perceive the utility of these devices to incorporate them into their daily lives. Hence, this study aims to identify users' perceptions regarding the acceptance of m-health technologies based on a synthesis of meta-analysis studies on the subject in the literature. Using the relations and constructs proposed in the UTAUT2 (Unified Theory of Acceptance and Use of Technology 2) technology acceptance model, the methodological approach utilized a meta-analysis to raise the effect of the main factors on the Behavioral Intention to Use m-health technologies. Furthermore, the model proposed also estimated the moderation effect of gender, age, and timeline variables on the UTAUT2 relations. In total, the meta-analysis utilized 84 different articles, which presented 376 estimations based on a sample of 31,609 respondents. The results indicate an overall compilation of the relations, as well as the primary factors and moderating variables that determine users' acceptance of the studied m-health systems.

Critical Success Factors for Successful Implementation of Healthcare 4.0: A Literature Review and Future Research Agenda.

The digitization of healthcare services is a major shift in the manner in which healthcare services are offered and managed in the modern era. The COVID-19 pandemic has speeded up the use of digital technologies in the healthcare sector. Healthcare 4.0 (H4.0) is much more than the adoption of digital tools, however; going beyond that, it is the digital transformation of healthcare. The successful implementation of H 4.0 presents a challenge as social and technical factors must be considered. This study, through a systematic literature review, expounds ten critical success factors for the successful implementation of H 4.0. Bibliometric analysis of existing articles is also carried out to understand the development of knowledge in this domain. H 4.0 is rapidly gaining prominence, and a comprehensive review of critical success factors in this area has yet to be conducted. Conducting such a review makes a valuable contribution to the body of knowledge in healthcare operations management. Furthermore, this study will also help healthcare practitioners and policymakers to develop strategies to manage the ten critical success factors while implementing H 4.0.

Effects of Lean Interventions Supported by Digital Technologies on Healthcare Services: A Systematic Review.

Despite the increasing utilization of lean practices and digital technologies (DTs) related to Industry 4.0, the impact of such dual interventions on healthcare services remains unclear. This study aims to assess the effects of those interventions and provide a comprehensive understanding of their dynamics in healthcare settings. The methodology comprised a systematic review following the PRISMA guidelines, searching for lean interventions supported by DTs. Previous studies reporting outcomes related to patient health, patient flow, quality of care, and efficiency were included. Results show that most of the improvement interventions relied on lean methodology followed by lean combined with Six Sigma. The main supporting technologies were simulation and automation, while emergency departments and laboratories were the main settings. Most interventions focus on patient flow outcomes, reporting positive effects on outcomes related to access to service and utilization of services, including reductions in turnaround time, length of stay, waiting time, and turnover time. Notably, we found scarce outcomes regarding patient health, staff wellbeing, resource use, and savings. This paper, the first to investigate the dual intervention of DTs with lean or lean-Six Sigma in healthcare, summarizes the technical and organizational challenges associated with similar interventions, encourages further research, and promotes practical applications.

Implementing a material planning and control method for special nutrition in a Brazilian public hospital.

This study aims to (i) propose a demand forecast model for special nutrition materials in the context of health services, and (ii) comparatively evaluate three inventory management and control systems (periodic review, continuous review and mixed) for special nutrition materials. For that, we carried out a case study in a Brazilian public teaching hospital where data and information collection were conducted over a span of 22 months (from January 2018 and were consolidated until October 2019). A six-step approach was followed to propose the demand forecasting models and, later, evaluate the inventory control systems for special nutrition materials. Results indicate that if the organization implements the proposed inventory management method, there could be savings of up to 33% in the stock values managed by the healthcare organization. This research shows the planning and control of special nutrition materials in an integrated manner. Demand forecasting methods have been combined with inventory management to promote systemic improvements to healthcare organization.

Professional Competence and Its Effect on the Implementation of Healthcare 4.0 Technologies: Scoping Review and Future Research Directions.

BACKGROUND: The implementation of Healthcare 4.0 technologies faces a number of barriers that have been increasingly discussed in the literature. One of the barriers presented is the lack of professionals trained in the required competencies. Such competencies can be technical, methodological, social, and personal, contributing to healthcare professionals managing and adapting to technological changes. This study aims to analyse the previous research related to the competence requirements when adopting Healthcare 4.0 technologies. METHODS: To achieve our goal, we followed the standard procedure for scoping reviews. We performed a search in the most important databases and retrieved 4976 (2011-present) publications from all the databases. After removing duplicates and performing further screening processes, we ended up with 121 articles, from which 51 were selected following an in-depth analysis to compose the final publication portfolio. RESULTS: Our results show that the competence requirements for adopting Healthcare 4.0 are widely discussed in non-clinical implementations of Industry 4.0 (I4.0) applications. Based on the citation frequency and overall relevance score, the competence requirement for adopting applications of the Internet of Things (IoT) along with technical competence is a prominent contributor to the literature. CONCLUSIONS: Healthcare organisations are in a technological transition stage and widely incorporate various technologies. Organisations seem to prioritise technologies for 'sensing' and 'communication' applications. The requirements for competence to handle the technologies used for 'processing' and 'actuation' are not prevalent in the literature portfolio.

Forecasting the length-of-stay of pediatric patients in hospitals: a scoping review.

BACKGROUND: Healthcare management faces complex challenges in allocating hospital resources, and predicting patients' length-of-stay (LOS) is critical in effectively managing those resources. This work aims to map approaches used to forecast the LOS of Pediatric Patients in Hospitals (LOS-P) and patients' populations and environments used to develop the models. METHODS: Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) methodology, we performed a scoping review that identified 28 studies and analyzed them. The search was conducted on four databases (Science Direct, Scopus, Web of Science, and Medline). The identification of relevant studies was structured around three axes related to the research questions: (i) forecast models, (ii) hospital length-of-stay, and (iii) pediatric patients. Two authors carried out all stages to ensure the reliability of the review process. Articles that passed the initial screening had their data charted on a spreadsheet. Methods reported in the literature were classified according to the stage in which they are used in the modeling process: (i) pre-processing of data, (ii) variable selection, and (iii) cross-validation. RESULTS: Forecasting models are most often applied to newborn patients and, consequently, in neonatal intensive care units. Regression analysis is the most widely used modeling approach; techniques associated with Machine Learning are still incipient and primarily used in emergency departments to model patients in specific situations. CONCLUSIONS: The studies' main benefits include informing family members about the patient's expected discharge date and enabling hospital resources' allocation and planning. Main research gaps are associated with the lack of generalization of forecasting models and limited reported applicability in hospital management. This study also provides a practical guide to LOS-P forecasting methods and a future research agenda.

Hospital Investment Decisions in Healthcare 4.0 Technologies: Scoping Review and Framework for Exploring Challenges, Trends, and Research Directions.

BACKGROUND: Alternative approaches to analyzing and evaluating health care investments in state-of-the-art technologies are being increasingly discussed in the literature, especially with the advent of Healthcare 4.0 (H4.0) technologies or eHealth. Such investments generally involve computer hardware and software that deal with the storage, retrieval, sharing, and use of health care information, data, and knowledge for communication and decision-making. Besides, the use of these technologies significantly increases when addressed in bundles. However, a structured and holistic approach to analyzing investments in H4.0 technologies is not available in the literature. OBJECTIVE: This study aims to analyze previous research related to the evaluation of H4.0 technologies in hospitals and characterize the most common investment approaches used. We propose a framework that organizes the research associated with hospitals' H4.0 technology investment decisions and suggest five main research directions on the topic. METHODS: To achieve our goal, we followed the standard procedure for scoping reviews. We performed a search in the Crossref, PubMed, Scopus, and Web of Science databases with the keywords investment, health, industry 4.0, investment, health technology assessment, healthcare 4.0, and smart in the title, abstract, and keywords of research papers. We retrieved 5701 publications from all the databases. After removing papers published before 2011 as well as duplicates and performing further screening, we were left with 244 articles, from which 33 were selected after in-depth analysis to compose the final publication portfolio. RESULTS: Our findings show the multidisciplinary nature of the research related to evaluating hospital investments in H4.0 technologies. We found that the most common investment approaches focused on cost analysis, single technology, and single decision-maker involvement, which dominate bundle analysis, H4.0 technology value considerations, and multiple decision-maker involvement. CONCLUSIONS: Some of our findings were unexpected, given the interrelated nature of H4.0 technologies and their multidimensional impact. Owing to the absence of a more holistic approach to H4.0 technology investment decisions, we identified five promising research directions for the topic: development of economic valuation methodologies tailored for H4.0 technologies; accounting for technology interrelations in the form of bundles; accounting for uncertainties in the process of evaluating such technologies; integration of administrative, medical, and patient perspectives into the evaluation process; and balancing and handling complexity in the decision-making process.

Digital technologies: An exploratory study of their role in the resilience of healthcare services.

Descriptions of resilient performance in healthcare services usually emphasize the role of skills and knowledge of caregivers. At the same time, the human factors discipline often frames digital technologies as sources of brittleness. This paper presents an exploratory investigation of the upside of ten digital technologies derived from Healthcare 4.0 (H4.0) in terms of their perceived contribution to six healthcare services and the four abilities of resilient healthcare: monitor, anticipate, respond, and learn. This contribution was assessed through a multinational survey conducted with 109 experts. Emergency rooms (ERs) and intensive care units (ICUs) stood out as the most benefited by H4.0 technologies. That is consistent with the high complexity of those services, which demand resilient performance. Four H4.0 technologies were top ranked regarding their impacts on the resilience of those services. They are further explored in follow-up interviews with ER and ICU professionals from hospitals in emerging and developed economies to collect examples of applications in their routines.

Operations Management teaching practices and information technologies adoption in emerging economies during COVID-19 outbreak.

The objective of this article is three-fold. First, it aims at identifying the main teaching practices and information and communication technologies (ICTs) used to teach Operations Management (OM) in emerging economies during COVID-19 outbreak. Second, it investigates the effect of contextual characteristics on the adoption level of those teaching practices and ICTs. Third, this study examines the relationship between the adoption of ICTs and OM teaching practices during COVID-19 outbreak. Expectedly, schools around the world have pivoted to online learning and digital classrooms. Thus, OM lecturers and professors located in emerging economies that have been teaching during COVID-19 outbreak were surveyed. The collected data was analyzed through multivariate techniques. Findings indicate that lecturers and professors have been remarkably adopting specific teaching practices and ICTs to teach OM. Nevertheless, when considering the contextual characteristics of the universities, departments, and lecturers/professors, the adoption level of those practices and ICTs may significantly vary, especially depending on subject type and teaching experience. Moreover, we empirically verified that ICTs positively relate with OM teaching practices in emerging economies, although in a much less extent than expected. This research provides OM instructors guidelines to better plan their courses and subjects in face of extreme disruptive moments, such as the one caused by the COVID-19. Understanding how the concurrent utilization of ICTs and teaching practices helps OM programs to continue developing their activities is particularly important for universities located in emerging economies, since they are more likely to struggle with resources scarcity and more financially humble students.

Impact of COVID-19 outbreak on employee performance - Moderating role of industry 4.0 base technologies.

COVID-19 outbreak has implied significant changes in the way service organizations work, affecting employees' routine and activities. At the same time, the advent of Industry 4.0 (I4.0) introduced new technologies that might facilitate such activities, mitigating the COVID-19's implications. The objective of this research is two-fold. First, we aim at examining the impact of COVID-19's work implications on employees' performance (i.e. output quality and delivery). Second, we seek to verify the moderating role of I4.0 base technologies on this relationship. We surveyed 106 employees of different service organizations who have been working remotely during the pandemic and analyzed their responses through multivariate techniques. Results revealed that COVID-19's work implications (i.e. home office work environment, job insecurity and virtual connection) do impact employee's performance, although not at the same extent. Further, we found that I4.0 technologies moderate the enhancement of employee's performance. However, the orientation and intensity of such moderation may vary according to the performance metric and work implication under analysis. As COVID-19 outbreak inevitably pushed new ways of working that can become an integral part of the post-pandemic world, our research provides important theoretical and practical implications for improving employee's performance through the digitalization of service organizations.

Assessing the Impact of Lean Healthcare on Inpatient Care: A Systematic Review.

Healthcare services are facing challenges in increasing their efficiency, quality of care, and coping with surges in demand. To this end, some hospitals have implemented lean healthcare. The aim of this systematic review is to evaluate the effects of lean healthcare (LH) interventions on inpatient care and determine whether patient flow and efficiency outcomes improve. The review was performed according to PRISMA. We used six databases to search for studies published from 2002 to 2019. Out of 5732 studies, 39 measuring one or more defined outcomes were included. Hospital length of stay (LOS) was measured in 23 studies, 16 of which reported a reduction, turnover time (TOT) decreased in six out of eight studies, while the turnaround time (TAT) and on-time starts (OTS) improved in all five and seven studies, respectively. Moreover, eight out of nine studies reported an earlier discharge time, and the boarding time decreased in all four cases. Meanwhile, the readmission rate did not increase in all nine studies. Lastly, staff and patient satisfaction improved in all eight studies. Our findings show that by focusing on reducing non-value-added activities, LH contributed to improving patient flow and efficiency within inpatient care.

Effects of Lean Healthcare on Patient Flow: A Systematic Review.

OBJECTIVES: To assess the effects of lean healthcare (LH) on patient flow in ambulatory care and determine whether waiting time and length of stay (LOS) decrease after LH interventions. METHODS: A systematic review was performed with close adherence to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We searched for studies of healthcare organizations applying LH interventions within ambulatory care published between 2002 and 2018. Six databases and grey literature sources were used. Two reviewers independently screened and assessed each study. When consensus was difficult to reach, a third reviewer intervened. Finally, a summary of findings was generated. RESULTS: Out of 5627 studies, 40 were included. Regarding LOS for all patients, 19 out of 22 studies reported a decrease. LOS for discharged patients decreased in 11 out of 13 studies, whereas LOS for admitted patients was reduced in 6 out of 7 studies. Waiting time for patients before seeing a healthcare professional decreased in 24 out of 26 studies. Waiting time to treatment and waiting time for appointments were minimized in 4 and 2 studies, respectively. Patients who left without being seen by a doctor decreased in 9 out of 12 studies. Finally, patient and staff satisfaction were measured in 8 and 2 studies, respectively, with each reporting improvements. CONCLUSIONS: According to our findings, LH helped to reduce waiting time and LOS in ambulatory care, mainly owing to its focus on identifying and minimizing non-value added (NVA) activities. Nevertheless, evidence of the impact of LH on patient/staff satisfaction and the translation of the obtained benefits into savings is scarce among studies.

Lean implementation in healthcare supply chain: a scoping review.

PURPOSE: The purpose of this paper is to identify the lean production (LP) practices applied in healthcare supply chain and the existing barriers related to their implementation. DESIGN/METHODOLOGY/APPROACH: To achieve that, a scoping review was carried out in order to consolidate the main practices and barriers, and also to evidence research gaps and directions according to different theoretical lenses. FINDINGS: The findings show that there is a consensus on the potential of LP practices implementation in healthcare supply chain, but most studies still report such implementation restricted to specific unit or value stream within a hospital. ORIGINALITY/VALUE: Healthcare organizations are under constant pressure to reduce costs and wastes, while improving services and patient safety. Further, its supply chain usually presents great opportunities for improvement, both in terms of cost reduction and quality of care increase. In this sense, the adaptation of LP practices and principles has been widely accepted in healthcare. However, studies show that most implementations fall far short from their goals because they are done in a fragmented way, and not from a system-wide perspective.

Lean-Oriented Layout Design of a Health Care Facility.

BACKGROUND: In this article, we propose a method that integrates systematic layout planning techniques to lean health care practices aided by multicriteria decision analysis that could be applied to reformulate the layout of health care facilities. METHODS: We analyze a high-variety sterilization unit of a large public hospital located in Brazil. The unit is currently implementing lean practices, and layout changes are required to provide more efficient materials and information flows. RESULTS: Traditional design of health care facilities is not aligned with lean implementation and its underlying practices and principles. We propose the integration of such approaches to enhance their benefits. To rank and select the best layout alternative, a multicriteria decision analysis method (analytic hierarchy process) is adopted. CONCLUSIONS: There are 3 contributions here: the integration of lean principles into traditional health care facility design practices, the use of multicriteria decision analysis to refine the determination of the best layout solution, and the application of our propositions in a real case study.

A Six Sigma Approach to Analyze Time-to-Assembly Variance of Surgical Trays in a Sterile Services Department.

INTRODUCTION: We analyze the assembly of surgical trays in a hospital's sterile services department. The department assembles 520 different tray setups. However, tray assembly times are unknown, imposing a challenge to production planners. To respond to demand, workers from other departments are often called, leading to higher operational costs and more frequent quality problems due to workers' poor training and inconsistency. METHODS: Conducting traditional time-motion studies is infeasible in such a high variety production setting. Thus, we used design of experiments to optimize the data acquisition. Assembly times of 36 trays were sampled using a 2-factor nested factorial design. Through regression analysis, we built a model to estimate completion times of trays not sampled in the experiment. RESULTS: A prediction model with 90.8% accuracy was obtained from the experimental data. The model was validated with assembly times from several trays not included in the experiment. Predicted assembly times had an absolute error of 7.83% on average compared with observed assembly times. CONCLUSIONS: Design of experiments and regression analysis combined were able to optimize time data acquisition using a small sample of trays, resulting in a model that predicted assembly times within an acceptable margin of error.